Plug-in Electric Vehicles Charging Load Research Articles

전기차 충전 장소를 고려한 그리드 일부하곡선 분석

This paper presents a methodology to calculate the daily load curve per city by taking into consideration a charging station for electric vehicles, which easily determines the effect of the load owing to the charging of electric vehicles in Seoul. In particular, we calculate the charging power of uncontrolled plug-in electric vehicles (PEVs) in terms of the daily running characteristics of vehicle travelling between homes and workplace, with respect to PEV charging stations in the city, according to the market share of PEVs. Furthermore, we calculate the load curve for the simultaneous charging strategy of controlled PEVs in terms of the vehicles’ daily running characteristics between homes and workplaces and a time-of-use (TOU) price plan of the Seoul Metropolitan Government under uncontrolled and controlled charging types. Thus, we are able to analysis the effect of the total existing electricity load and the abovementioned daily load on the grid. Because we can precisely determine the effect of the hourly charging load of PEVs on a power grid in Seoul using these study results, we can establish a PEV charging load management plan to prevent power grid reinforcement and expansion while satisfying the overload constraint of the power grid in Seoul using an appropriate TOU price plan.

What do consumers think of smart charging? Perceptions among actual and potential plug-in electric vehicle adopters in the United Kingdom

Widespread adoption of Plug-in Electric Vehicles (PEVs) would add substantially to overall electricity demand, while increasing deployment of renewable supply sources will make supply-demand balancing more difficult. Early PEV market experience suggests that users preferentially charge their vehicles in the early evening, when other demands are high. Managed (or Smart) charging aims to shift PEV charging load to times when other demands are low, to facilitate better integration into the wider energy system, operation within network constraints, and minimisation of future network reinforcement costs. However, material effectiveness would require mass engagement with managed charging. To gain initial insight into the potential for managed charging, 60 semi-structured interviews were carried out with actual or potential UK PEV users. Interviews explored present charging behaviour and responses to two types of managed charging schemes, user-managed charging (UMC) based on time-of-use tariffs, and supplier-managed charging (SMC). Participants’ willingness to engage with either was conditional on large reductions in charging costs. UMC was preferred over SMC, because of perceived personal control and lower perceived risk that a vehicle might not be fully charged at the required time. Preference for SMC was based mainly on perceived advantages to society as a whole.

Direct Control of Plug-In Electric Vehicle Charging Load Using an In-House Developed Intermediate Control Unit

Unscheduled charging of a high number of plug-in electric vehicles (PEVs) can raise the peak electric load and affect the power quality (PQ) of the distribution power grids. This necessitates devising novel solutions to support the power grids when PEVs are being charged by controlling the PEVs’ charging load. In this paper, an intermediate control unit for the commercial battery chargers is developed in-house, which can directly control the PEV charging load by modifying the power levels during ac charging. Furthermore, field measurements are conducted to investigate the impacts of mass-produced PEVs on the point of common coupling during charging by the developed unit with different power levels. In addition, a home charging management system that employs the developed unit is designed. The results from the field experiments, together with the model-based case studies, demonstrate that the developed unit can be readily adopted for direct control of the charging loads of mass-produced PEVs, without the modification of the existing recharging equipment. Moreover, in the context of charging management, the electricity cost can be minimized, whilst the preferences of the PEV owners can be realized and the PQ of the distribution networks can be maintained simultaneously.

Dual‐optimisation of power sources including plug‐in electric vehicles and renewable energy resources at transmission‐level system

With the growing trend of plug-in electric vehicles (PEVs), the charging load of PEVs can have a huge impact on current transmission-level system. In the meantime, there also comes a great potential in the optimisation aspect for both power generation economic and power transmission safety concerns. Here, a dual-optimisation algorithm is developed to minimise the total production cost of power sources including renewable energy resources (RER) and PEV cluster. In the meantime, the overloading in transmission lines and transformers is avoided. Linear programming and DC optimal power flow (DCOPF) are separately applied to step one and step two optimisation. The simulation result from a modified IEEE 9-bus system reveals that dual-optimisation method successfully reduced the production cost based on a hybrid model of power grid in step one optimisation. In step two optimisation, the overloaded transmission line is detected and held at capacity limit to prevent overheating. In conclusion, in dual-optimisation algorithm, PEVs can serve as both the energy storage device and the energy supply device. Consequently, the total production cost can be reduced, and the optimal power flow can be obtained.

Mitigation of the Impact of High Plug-in Electric Vehicle Penetration on Residential Distribution Grid Using Smart Charging Strategies

Vehicle electrification presents a great opportunity to reduce transportation greenhouse gas emissions. The greater use of plug-in electric vehicles (PEVs), however, puts stress on local distribution networks. This paper presents an optimal PEV charging control method integrated with utility demand response (DR) signals to mitigate the impact of PEV charging to several aspects of a grid, including load surge, distribution accumulative voltage deviation, and transformer aging. To build a realistic PEV charging load model, the results of National Household Travel Survey (NHTS) have been analyzed and a stochastic PEV charging model has been defined based on survey results. The residential distribution grid contains 120 houses and is modeled in GridLAB-D. Co-simulation is performed using Matlab and GridLAB-D to enable the optimal control algorithm in Matlab to control PEV charging loads in the residential grid modeled in GridLAB-D. Simulation results demonstrate the effectiveness of the proposed optimal charging control method in mitigating the negative impacts of PEV charging on the residential grid.

Analysis for Evaluating the Impact of PEVs on New-Town Distribution System in Korea

This paper analyzes the impact of Plug-in Electric vehicles(PEVs) on power demand and voltage change when PEVs are connected to the domestic distribution system. Specifically, it assesses PEVs charging load by charging method in accordance with PEVs penetration scenarios, its percentage of total load, and voltage range under load conditions. Concretely, we develop EMTDC modelling to perform a voltage distribution analysis when the PEVs charging system by their charging scenario was connected to the distribution system under the load condition. Furthermore we present evaluation algorithm to determine whether it is possible to adjust it such that it is in the allowed range by applying ULTC when the voltage change rate by PEVs charging scenario exceed its allowed range. Also, detailed analysis of the impact of PEVs on power distribution system was carried out by calculating existing electric power load and additional PEVs charge load by each scenario on new-town in Korea to estimate total load increases, and also by interpreting the subsequent voltage range for system circuits and demonstrating conditions for countermeasures. It was concluded that total loads including PEVs charging load on new-town distribution system in Korea by PEVs penetration scenario increase significantly, and the voltage range when considering ULTC, is allowable in terms of voltage tolerance range up to a PEVs penetration of 20% by scenario. Finally, we propose the charging capacity of PEVs that can delay the reinforcement of power distribution system while satisfying the permitted voltage change rate conditions when PEVs charging load is connected to the power distribution system by their charging penetration scenario.

Optimal Coordination of Plug-In Electric Vehicles in Power Grids With Cost-Benefit Analysis—Part I: Enabling Techniques

Plug-in electric vehicles (PEVs) appear to offer a promising option for mitigating greenhouse emission. However, uncoordinated PEV charging can weaken the reliability of power systems. The proper accommodation of PEVs in a power grid imposes many challenges on system planning and operations. This work aims to investigate optimal PEV coordination strategies with cost-benefit analysis. In Part I, we first present a new method to calculate the charging load of PEVs with a modified Latin hypercube sampling (LHS) method for handling the stochastic property of PEVs. We then propose a new two-stage optimization model to discover the optimal charging states of PEVs in a given day. Using this model, the peak load with charging load of PEVs is minimized in the first stage and the load fluctuation is minimized in the second-stage with peak load being fixed as the value obtained in the first stage. An algorithm based on linear mixed-integer programming is provided as a suitable solution method with fast computation. Finally, we present a new method to calculate the benefit and cost for a PEV charging and discharging coordination strategy from a social welfare approach. These methods are useful for developing PEV coordination strategies in power system planning and supporting PEV-related policy making.